Introduction

The terms transgender and gender diverse (TGD) refer to individuals whose gender identity does not align with the sex assigned to them at birth. These broad categories include individuals who may identify within the binary system (as male or female), embrace a non-binary identity, or not align with any gender at all1,2. TGD individuals face significant structural, interpersonal, social, and legal barriers within healthcare systems3. These barriers hinder access to gender-affirming care and perpetuate health inequities by failing to address TGD-specific health needs4,5. The gender minority stress model links chronic stressors such as stigma, victimization, and societal discrimination to adverse health outcomes in TGD individuals, including increased risks of anxiety, depression, self-harm behaviors, suicidality2,6, trauma7,8, substance abuse9, and stress-related health issues over the lifespan10. Addressing these challenges is essential to ensure that TGD people have access to gender-affirming pathways and affirming care.

Mobile health (mHealth) applications offer innovative solutions to bridge these gaps in healthcare. These digital tools can be designed specifically to deliver competent, affirming care by providing resources tailored to the unique needs of TGD people. Additionally, they educate both healthcare professionals and users, equipping providers with training to reduce discrimination and improve care quality. For TGD users, mHealth apps provide accurate information that combats misinformation and fosters informed decision-making.

One of the key advantages of mHealth apps is their accessibility via smartphones, making them especially effective for individuals in areas where gender-affirming care is unavailable11. They also help standardize care across regions with differing policies, reducing barriers such as unequal insurance coverage and restrictive regulations12,13,14. For socioeconomically disadvantaged groups, these apps present scalable, cost-effective solutions. Furthermore, their ability to offer privacy and discretion protects users in unaccepting environments or those not yet out, reducing the risk of stigma and rejection. Functionalities such as diagnostic support, decision-making tools, behavior change facilitation, and treatment adherence aids make mHealth apps effective for chronic care management15,16. Research has shown their effectiveness in improving symptoms, enhancing treatment adherence, and reducing hospitalizations17, underscoring their potential to enhance access to gender-affirming care.

Despite their potential, existing mHealth applications often fail to adequately address the needs of TGD individuals. Many apps lack inclusivity, offering limited customization options that may restrict users to binary gender identities. Some platforms enforce “real name policies”, requiring identity verification through official documentation which prevents users from selecting their preferred names or pronouns18, leading to privacy violations, misgendering, or the risk of being outed19. Facial recognition technologies also pose challenges, as they often rely on datasets that fail to represent diverse gender presentations, resulting in misclassification or exclusion of TGD users20. Algorithmic biases in content recommendations and advertising further perpetuate discrimination, while inadequate moderation on forums exposes users to cyberbullying and transphobia21,22. Moreover, many mHealth apps operate on assumptions of binary anatomy, excluding individuals with diverse medical experiences.

A growing body of literature has emerged that warrants systematic examination. Existing reviews have predominantly concentrated on specific domains, such as HIV prevention23,24, or on applications developed outside academic contexts that lack a robust theoretical foundation23. Considering the rapid evolution of digital health technologies, numerous innovations may have occurred in the relatively short period since the most recent review on this subject25. To bridge this gap and incorporate newly developed applications, we conducted the present systematic review. Our analysis focused primarily on mHealth applications originating from academic environments, given their theoretical grounding and methodological rigor. Nevertheless, we also investigated commercially developed applications, frequently created by allies of TGD communities or community members themselves, through searches on platforms such as Google Play and the Apple App Store. These results are presented in Supplementary Table I, as no standardized methodology currently exists for their retrieval from the scientific literature.

This study presents a comparative analysis of 11 mHealth applications developed for TGD individuals. We classify the apps based on their effectiveness in addressing four key healthcare barriers: structural, interpersonal, economic, and informational. This classification provides clear guidance for researchers and developers aiming to enhance healthcare accessibility for TGD people. Our analysis identifies two distinct trends: apps designed to reduce the impact of stressors and those that promote resilience factors. We outline potential strategies to further develop both approaches. By systematically organizing and comparing app features and their underlying theoretical frameworks, this review offers practical insights for researchers, developers, and policymakers to develop solutions that meet TGD needs while implementing evidence-based strategies to improve user engagement, satisfaction, and overall app effectiveness. A comprehensive quality assessment was conducted to identify existing gaps and limitations, offering recommendations to address these shortcomings and support the selection of appropriate implementation protocols. Furthermore, this review takes a forward-looking approach, proposing future research directions and practical improvements to strengthen current practices. Unlike previous reviews, this study addresses a wider range of health needs. To the best of our knowledge, this is the first comprehensive review of its kind, offering a foundational reference for advancing mHealth interventions for TGD individuals.

Results

Need to strengthen provider networks and challenge stigma and discrimination in healthcare settings

The reviewed applications commonly targeted structural barriers (e.g., limited access to healthcare in underserved areas), interpersonal barriers (e.g., experiences of stigma and misgendering), economic barriers (e.g., high costs and lack of insurance), and informational barriers (e.g., limited awareness of inclusive, evidence-based resources), as summarized in Table 1. Educational content and skill-building modules were central components of these interventions, designed to enhance health literacy, self-efficacy, and user empowerment. This allows patients to overcome misinformation and make informed decisions about their health. Key strategies to achieve these goals included the use of gamification and interactive techniques, such as role-playing scenarios, to increase user engagement, support mental health management26,27, and promote communication strategies27.

Table 1 Healthcare accessibility
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Several mHealth apps specifically addressed the prevention and management of sexually transmitted infections (STIs), aiming to bypass health inequities stemming from systemic barriers such as stigma and discrimination in healthcare settings26,27,28,29,30,31. These barriers often limit access to preventive care, contributing to higher rates of STIs among TGD individuals. By incorporating features such as HIV prevention education, self-testing guidance, and PrEP information, these apps enhanced self-care and accessibility. While the reviewed apps address key barriers, they primarily focus on individual-level interventions, often overlooking systemic factors such as provider education and structural discrimination. A notable limitation is the insufficient integration of mHealth apps with healthcare providers. These gaps underscore the need to actively challenge stigma within healthcare settings, foster therapeutic alliances, and strengthen connections between users and providers.

Lack of TGD-specific theoretical frameworks

A variety of theoretical frameworks informed the development of mHealth applications to ensure alignment between functionalities, user needs, and targeted health outcomes. Behavioral, cognitive, and empowerment models underpinned features aimed at facilitating personalized interventions, goal setting, and risk reduction26,27,28. Gamification strategies were integrated to enhance sustained user engagement through interactive components and reward systems27. Human-centered and participatory design methodologies were employed to optimize usability, foster inclusivity, and ensure relevance to the target community26,29,32,33,34,35. Iterative development approaches, including the AGILE and Health-ITUES models, supported continuous integration of user feedback, thereby improving accessibility, adaptability, and overall user experience26,27,33,34,35. Details about specific frameworks can be found in Table 2.

Table 2 mHealth features
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The reviewed studies demonstrate progress in integrating technical and theoretical frameworks to guide app development. However, many apps lack clear theoretical grounding, limiting their ability to comprehensively address TGD health needs. Notably, only one study employed a theoretical framework specifically developed for TGD individuals10,32, while the remaining studies failed to incorporate approaches that adequately address the unique experiences and challenges faced by these people.

Failure to implement systemic healthcare changes and underexploration of stressors and protective factors

Many applications aimed to reduce stigma and discrimination by incorporating tools such as feedback systems and peer navigation mechanisms27,28,29,34,35,36, through which individuals could support each other in identifying competent and affirming healthcare providers28,29,36, overcoming barriers to HIV care30, and navigating discriminatory scenarios in clinical settings. These modules were designed to develop effective communication strategies and increase awareness of personal triggers, emotions, and responses27.

Other applications focused on fostering pride and community connection by incorporating interactive modules27 or tools that promoted peer support networks34,35. These platforms facilitated connections with trusted individuals, provided opportunities to report incidents of discrimination or violence, and allowed users to share experiences within supportive and affirming environments.

Mental health support was another key focus of these interventions28,29,32, with applications offering resources to reduce social isolation and real-time monitoring of stressors and suicide risk factors32 to aid in suicide prevention.

The reviewed apps highlight progress in addressing stigma and fostering community connection but lack a focus on systemic healthcare changes, such as integrating gender-affirming, evidence-based practices into medical settings, improving policy advocacy, and expanding access to legal and financial resources. Moreover, they underexplore protective factors, relying primarily on community connectedness and pride.

Key methodological limitations and insufficient evaluation of health outcomes

An overview of the quality assessment, based on total MMAT scores, is presented in Table 3. The distribution of scores included one study33 rated as very low (40%), two studies28,36 rated as moderate (60%), four studies26,27,30,34 rated as moderate-high (80%), and four studies28,29,31,32,35 rated as high (100%). Despite these generally positive rankings, we identified significant limitations. While most studies reported high usability and satisfaction scores, they often lacked rigorous evaluation of health outcomes. Common issues included the absence of baseline measurements, short exposure and follow-up periods, small and geographically limited samples, and reliance on self-reported data. None of the studies included control groups, which limited meaningful comparisons with standard care. Moreover, among the studies utilizing mixed methods26,27,33,34, none adequately justified their choice of this approach. Additionally, studies employing quantitative non-randomized designs28,29,30 failed to address confounders in their design and analysis. Data related to the study design and methodology are summarized in Table 4.

Table 3 Overview of study quality assessment using the MMAT
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Table 4 Study Characteristics
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The studies predominantly evaluated usability and user satisfaction. Across these measures, the apps consistently demonstrated high usability and acceptability, indicating strong alignment with user expectations and needs. Follow-up methodologies varied, including interviews, surveys, and app usage data, with evaluation periods ranging from short-term assessments27,32,33 to long-term follow-ups28,29,30,31. Details of the measurement metrics can be found in Table 2.

However, direct health and well-being outcomes were infrequently measured. The only study reporting significant health changes28demonstrated that peer navigation led to increased HIV testing, PrEP uptake, and engagement in HIV care, with sustained effects observed up to nine months post-intervention.

These findings highlight the need for more rigorous and comprehensive evaluations of health outcomes in future research26,28,29,32,33,34.

Discussion

Our analysis identifies four key barriers to healthcare access for TGD individuals that these mHealth applications aim to address: structural, interpersonal, economic, and informational. (1) Structural barriers are addressed through features that help locate gender-affirming healthcare services using interactive maps to identify competent providers. Additionally, some apps offer self-administered diagnostic kits, enabling individuals to bypass healthcare facilities, thus facilitating access for underserved populations or those seeking greater privacy. However, these kits risk weakening connections with providers and limiting outreach to vulnerable groups. Telemedicine present a potential solution, enabling personalized care and addressing access barriers that are often influenced by regional policies and healthcare infrastructure. (2) To reduce interpersonal barriers, such as stigma and discrimination, many apps adopt inclusive and affirming language and incorporate community consultation approaches to gain valuable perspectives. Some apps also implement peer-navigation systems to foster supportive relationships, build trust, and alleviate anxiety associated with healthcare interactions. However, these apps often focus on the individual rather than educating the broader environment and healthcare providers, failing to address the stigma and discrimination encountered in physical spaces and thereby perpetuating these barriers. Future mHealth apps should address this gap by promoting the creation of safe physical spaces and implementing training programs for healthcare providers to reduce discriminatory practices. (3) Economic barriers are mitigated by providing low-cost or free solutions for prevention and treatment, including self-administered kits, which reduce expenses related to in-person healthcare visits. (4) Lastly, mHealth apps address informational barriers by offering accurate, contextualized educational resources. This is identified as a strength in the reviewed articles, as these tools empower users to make informed health decisions and enhance their self-management of care.

The present review identifies key features prioritized by researchers to develop mHealth applications specifically addressing TGD needs. The studies analyzed emphasize the importance of using theoretical frameworks to guide the development of effective interventions. However, these frameworks are not always clearly defined, and some apps lack explicit theoretical grounding, limiting their ability to comprehensively address complex health needs. Notable examples of the application of theoretical frameworks include Meyer’s minority stress framework10 and behavioral and cognitive theories that empower users through education, goal setting, and skill development activities, fostering empowerment, self-efficacy, and informed decision-making. Most studies adopt participatory approaches, actively involving TGD individuals in the design and development process. Such approaches have been shown to effectively address health disparities in marginalized populations by promoting changes in community practices, programs, and systems37. This is particularly important for TGD individuals, who have historically faced marginalization38 and the medicalization of their identities, leading to distrust in academic and medical contexts39. By fostering trust and collaboration, participatory methods improve satisfaction with both processes and outcomes40,41, ensuring solutions align with user needs.

Two theoretical frameworks that can be employed to understand the mental and physical health challenges faced by TGD individuals are the Gender Minority Stress Model10 and the Social Safety Model42. The Gender Minority Stress Model suggests that chronic stress stems from societal stressors, both proximal and distal, that negatively impact mental and physical health. In contrast, the Social Safety Model highlights that adverse health outcomes result from a lack of social safety, which includes reliable connections, inclusion, and protection. Both models emphasize the need to reduce environmental stressors, particularly stigma and discrimination, while promoting social safety and protective factors. Research on the health of TGD individuals has historically prioritized the examination of risk factors, including body dysphoria and minority stress. More recently, however, there has been a paradigmatic shift toward recognizing and valuing positive experiences, such as gender euphoria, and moving away from pathologizing conceptualizations of TGD identities. Despite this emerging perspective, preventive interventions frequently continue to emphasize risk mitigation over the promotion of resilience at both individual and collective levels. The TRIM model43 identifies protective factors: at the group level, these include social support, community belonging (in-person, online, or through media)44, family acceptance, activism, and positive role models. At the individual level, factors such as self-worth, self-acceptance, pride, self-definition, hope, and gender affirmation pathways foster resilience. Integrating these elements into interventions could enhance support for TGD individuals. Two primary trends emerge from the mHealth apps reviewed: some focus on reducing stigma, discrimination, and violence, while others build support networks and foster community engagement. However, these apps primarily target individuals rather than addressing systemic issues. Since chronic stress is a societal product, rooted in the environments these individuals inhabit, a significant gap remains: mHealth interventions rarely promote environmental change, such as training competent professionals, reducing institutional discrimination, or fostering inclusive practices at a societal level. Future apps should integrate features that actively promote systemic change. Moreover, both the stressors and protective factors identified by the three models should be considered comprehensively to enable multifaceted interventions aimed at promoting the well-being of TGD individuals. This can be achieved by addressing issues such as internalized transphobia, promoting disclosure, reframing negative expectations for the future, fostering affirmation, and reducing victimization and rejection, while simultaneously expanding the focus on resilience factors identified by the TRIM model.

There are significant methodological limitations in the studies reviewed. Many report high usability and satisfaction scores on standardized metrics such as the System Usability Scale (SUS) and the Post-Study System Usability Questionnaire (PSSUQ), reflecting the success of these strategies in addressing usability challenges. However, while usability and user satisfaction are prioritized, rigorous evaluation of health outcomes is often lacking. A common limitation is the absence of baseline measurements, hindering the ability to assess changes over time and increasing the risk of outcome bias. In mental health-focused studies, failure to account for pre-existing conditions such as depression or anxiety may further confound intervention effects and undermine validity. Most studies have short exposure and follow-up periods, typically ranging from two weeks to three months, limiting long-term effect assessments. Discussions on statistical power are often absent, particularly in quantitative or mixed-method designs, with sample sizes frequently under 20 participants and recruitment confined to geographically limited areas, reducing generalizability. Convenience sampling predominates, potentially skewing results toward participants who are more technologically proficient and possess greater resource access. Many studies rely on self-reported data, which can introduce biases. Notably, none of the reviewed studies include control groups, limiting meaningful comparisons with standard care. This gap may stem from challenges in implementing randomized controlled trials (RCTs) for mHealth interventions tailored to TGD individuals, including recruitment difficulties, high costs, and ethical complexities. These barriers are exacerbated by a lack of supportive health policies, which often adopt a welfarist perspective, focusing on minimal provisioning rather than proactively supporting gender-affirming care. Addressing these challenges requires coordinated efforts among academic institutions, healthcare providers, and TGD organizations.

Despite the authors’ efforts to incorporate intersectionality and develop resources tailored to specific groups, such as transgender people of color (TPOC), there remains considerable room for improvement in terms of diversity and representation. Many studies fail to adequately include a broad range of demographic groups. For example, non-binary individuals are often underrepresented, despite their need for application features that explicitly affirm their identities, including gender-neutral language and tailored health resources. Similarly, the distinct needs of both older and younger TGD individuals warrant focused attention, necessitating the development of applications with supportive, age-appropriate interventions. A particularly notable gap is the underrepresentation of TGD individuals under the age of 18. Although digital interventions targeting minors do exist, as identified in the reviews by Skeen et al.45 and Skeen and Cain23, these are frequently developed outside academic settings (e.g., QueerViBE46, Queer Doc47, and Binder Reminder48) by private entities or community-based organizations. As such, they did not meet the inclusion criteria of our systematic review, which focused exclusively on peer-reviewed academic studies. To the best of our knowledge, following the completion of our database search, a study was published in which the MyPEEPS Mobile app, originally developed for same-sex-attracted adolescent males, was adapted for transmasculine youth aged 13 to 1849. The app was found to be highly usable and perceived as potentially effective in targeting HIV risk behaviors. The scarcity of studies within academic contexts may be driven by the ethical complexities associated with digital data collection involving minors41. Recruitment challenges further compound this issue, as accessing this population often requires collaboration with organizations, schools, or healthcare institutions, which adds procedural complexity. These barriers risk excluding a demographic that, as native digital users, stands to benefit significantly from mobile health interventions, thereby limiting the potential to address their unique needs effectively. Given the high prevalence of mobile technology use among adolescents, who now have unprecedented access to vast amounts of information but often possess limited capacity to assess the reliability of these sources compared to the past, future research should prioritize the development and evaluation of mHealth applications tailored to this age group. Additionally, many studies make implicit assumptions regarding technology access, presuming consistent availability of smartphones and stable internet connectivity, which may not reflect the lived realities of all TGD individuals.

To address existing limitations, future research should prioritize larger, more diverse samples through inclusive recruitment strategies, especially targeting rural and underserved populations. Employing rigorous study designs with baseline measurements, control groups, and validated outcome assessment tools will enhance methodological quality. Long-term follow-ups, supported by sustained funding and partnerships with public and private healthcare providers, are essential for evaluating sustainability and health impacts. Strengthening collaboration between academic institutions, developers, TGD communities, and policymakers is imperative, as lack of coordination can compromise healthcare outcomes50. This systematic review highlights progress in mHealth apps for TGD individuals, demonstrating their potential to reduce healthcare barriers through inclusive features and community-driven approaches. Academic apps primarily address public health issues such as HIV prevention and violence reduction, while commercial apps, Supplementary Table I, focus on everyday needs like tracking gender affirmation progress, mental health support, and voice training. Integrating both approaches could produce comprehensive, evidence-based tools that meet critical health needs and provide personalized support, ultimately enhancing the well-being of TGD individuals.

A limitation of this study is that the review protocol was not registered before its initiation.

Methods

To effectively meet the unique needs of TGD individuals, mHealth apps must prioritize inclusivity and sensitivity in their design. To guide the development of mHealth apps that address these needs, we propose a systematic review focusing on the key features prioritized by researchers. Specifically, this review aims to:

  • Identify common theoretical and technical frameworks used in apps development and design.

  • Review the types of health outcomes measured in evaluations of these apps, including usability and acceptability, and assess their quality.

  • Analyze how app features improve access to healthcare systems and help remove barriers.

Information source

This systematic review followed the PRISMA 2020 guidelines51 and employed a comprehensive search strategy across PubMed, Ebsco, Embase, and Scopus using Boolean operators. The PICO framework52 was used to formulate precise search terms focusing on the Population (P), Intervention (I), and Outcomes (O), while excluding Comparisons (C) since the main focus of the research was to explore the design and development aspects of mobile health applications for TGD people. The Population included transgender and gender diverse individuals, with the following search terms: “transgender*”, “transwom*”, “transm*”, “transsexual*”, “gender divers*”, “gender nonconform*”, “genderqueer”, “non-binary”, and “gender dysphor*”. Despite some terms being outdated or disrespectful, they were included to capture older studies or those from regions where these terms are still in use; The Intervention (I) terms focused on mobile health technologies, using “mobile application*”, “smartphone application*”, “mHealth”, and “mobile health”; The Outcome (O) terms targeted the development and user evaluation of mHealth applications, using: “develop*”, “design*”, “beta test*”, “usability”, and “acceptability”.

Study selection and search strategy

A total of 5005 records were identified through database searches conducted on May 5, 2024. The databases included PubMed (n = 609), EBSCO (n = 252), Scopus (n = 2949), and Embase (n = 1195). After removing duplicates, 3569 records remained. These were then screened based on their titles and abstracts, with two authors, MB and MM, independently applying the inclusion criteria. During this stage, 3412 records were excluded as they did not meet the review’s scope. No discrepancies occurred between the reviewers during this stage, as all articles with ambiguous eligibility were included for further screening. The remaining 157 records underwent additional screening based on their titles, abstracts, and preliminary full-text review. Discrepancies arose for two articles regarding whether apps with indirect contributions to well-being, such as those locating gender-neutral restrooms, should be classified as mHealth apps. After discussion and consultation with the third author, AG, it was determined that such apps did not meet the definition of mHealth apps and were excluded. In the final stage, 30 articles underwent full-text review. In cases where access to specific articles was restricted, the authors of those articles were contacted. This occurred for three articles: two were successfully obtained through correspondence with Jones28,29, but the article by Baione53 was excluded due to lack of response. Discrepancies also emerged regarding three studies that tested existing apps for feasibility with TGD individuals but did not specifically design or develop apps for their needs. These studies were excluded after discussion and consensus with AG, as the primary aim of the review was to evaluate the design and development of mHealth apps tailored to TGD individuals. Of the remaining studies, 21 articles were excluded for not meeting the inclusion criteria and were categorized with reasons for exclusion: “wrong population” (e.g., studies not involving TGD individuals), “apps for sexually transmitted diseases which were generally designed for broader populations and not specifically tailored to TGD individuals”), “not focused on TGD health” (if the primary focus was not on the health of transgender and gender-diverse individuals), “no app development involved” (e.g., protocols for future studies, or exploratory research that did not develop a smartphone mHealth app), and “article inaccessible” (if the criteria were met but the full article could not be accessed; attempts to contact the authors were unsuccessful). Two additional studies were identified through in-text citations, bringing the total to 11 articles that met the inclusion criteria and were included in the systematic review Fig.1.

Fig. 1: PRISMA flowchart of the systematic search.
figure 1

Illustrates the systematic review process based on the PRISMA 2020 guidelines, detailing the identification phase in which 5005 records were retrieved from four databases (PubMed, EBSCO, Scopus, and Embase) and an additional two records were identified through manual searches of in-text citations; the screening phase, during which 3569 records were assessed for relevance, resulting in 3412 exclusions and 154 records sought for retrieval, of which 124 were not retrievable; and the eligibility phase, where 30 records were evaluated for inclusion, with 19 excluded due to factors such as wrong population, focus on sexually transmitted diseases, lack of app development, non-relevance to transgender and gender-diverse health, or inaccessibility of articles, ultimately resulting in the inclusion of 11 studies in the review.

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Eligibility criteria

To be included in this systematic review, studies had to meet the following criteria: (a) involve mHealth smartphone applications, including web apps that could be installed on smartphones; (b) be specifically designed or adapted to support TGD individuals; (c) address physical or mental health concerns; and (d) focus on areas such as health monitoring, disease management, or access to health information, or any other purpose directly benefiting the health of TGD people. (e) Studies employing quantitative, qualitative, or mixed-methods approaches, including pilot and feasibility studies, were eligible, (f) provided they were peer-reviewed articles reporting outcome measures (study protocols were excluded). (g) Studies from any geographic location or publication date were included, (h) provided they were written in English, Italian, Portuguese, or Spanish (languages understood by the authors).

Criterion (a) was selected to ensure access to native smartphone functionalities, including push notifications, GPS, cameras, health sensors, real-time monitoring, and offline access. Smartphones, being widely accessible and often the primary tool for accessing digital resources, are essential for reaching diverse users across different geographic and socioeconomic contexts54.

Exclusion criteria included: (a) apps not designed for TGD individuals; (b) apps focused on sexually transmitted disease interventions not tailored to TGD needs; (c) non-health-related apps for TGD individuals; and (d) apps solely for telemedicine, telehealth, or messaging interventions.

Data extraction

The data extraction process was conducted independently by two reviewers, MB and MM, who extracted relevant information from each full-text article and assessed the risk of bias. Data related to study design and methodology were summarized in Table 4, while Table 2, presents a detailed overview of the types of mHealth apps examined, their functionalities, and the outcomes reported in the studies.

This systematic review included 11 studies26,27,28,29,30,31,32,33,34,35,36 focused on developing and testing mHealth applications for TGD individuals. The apps addressed challenges such as gender-affirming healthcare access36, HIV prevention and education26,27,28,29,30,31, suicide prevention32, credible health information33, improved communication34, and safety35. Most studies were conducted in the United States (n=9), with two conducted in Brazil. Participants were primarily young adults aged 18-34, although some studies included individuals aged 16-5526,34. Sample sizes ranged from 6 to 60, with ethnically diverse representation, including Black, Latinx, and Asian participants27,28,29,30,31,32,34.

Quality Assessment

We evaluated all the studies using the Mixed Methods Appraisal Tool (MMAT)55, which assesses the methodological quality of qualitative, quantitative, and mixed-methods studies. The MMAT consists of five items, with responses categorized as “yes,” “no,” or “can’t tell.” Consistent with prior scoping reviews56,57, we calculated quality based on the percentage of criteria met by each study. Ratings were classified as very low (20%), low (40%), moderate (60%), moderate-high (80%), and high (100%). The assessments were conducted independently by MB and MM, achieving a Cohen’s kappa (κ=0.82), reflecting substantial agreement. Any discrepancies were resolved through discussion.